Aminoglycoside-driven biosynthesis of selenium-deficient Selenoprotein P

Selenoprotein biosynthesis relies on the co-translational insertion of selenocysteine in response to UGA codons. Aminoglycoside antibiotics interfere with ribosomal function and may cause codon misreading. We hypothesized that biosynthesis of the selenium (Se) transporter selenoprotein P (SELENOP) is particularly sensitive to antibiotics due to its ten in frame UGA codons. As liver regulates Se metabolism, we tested the aminoglycosides G418 and gentamicin in hepatoma cell lines (HepG2, Hep3B and Hepa1-6) and in experimental mice. In vitro, SELENOP levels increased strongly in response to G418, whereas expression of the glutathione peroxidases GPX1 and GPX2 was marginally affected. Se content of G418-induced SELENOP was dependent on Se availability, and was completely suppressed by G418 under Se-poor conditions. Selenocysteine residues were replaced mainly by cysteine, tryptophan and arginine in a codon-specific manner. Interestingly, in young healthy mice, antibiotic treatment failed to affect Selenop biosynthesis to a detectable degree. These findings suggest that the interfering activity of aminoglycosides on selenoprotein biosynthesis can be severe, but depend on the Se status, and other parameters likely including age and general health. Focused analyses with aminoglycoside-treated patients are needed next to evaluate a possible interference of selenoprotein biosynthesis by the antibiotics and elucidate potential side effects

Statin and rottlerin small-molecule inhibitors restrict colon cancer progression and metastasis via MACC1

MACC1 (Metastasis Associated in Colon Cancer 1) is a key driver and prognostic biomarker for cancer progression and metastasis in a large variety of solid tumor types, particularly colorectal cancer (CRC). However, no MACC1 inhibitors have been identified yet. Therefore, we aimed to target MACC1 expression using a luciferase reporter-based high-throughput screening with the ChemBioNet library of more than 30,000 compounds. The small molecules lovastatin and rottlerin emerged as the most potent MACC1 transcriptional inhibitors. They remarkably inhibited MACC1 promoter activity and expression, resulting in reduced cell motility. Lovastatin impaired the binding of the transcription factors c-Jun and Sp1 to the MACC1 promoter, thereby inhibiting MACC1 transcription. Most importantly, in CRC-xenografted mice, lovastatin and rottlerin restricted MACC1 expression and liver metastasis. This is—to the best of our knowledge—the first identification of inhibitors restricting cancer progression and metastasis via the novel target MACC1. This drug repositioning might be of therapeutic value for CRC patients

Insights into the Physiology and Ecology of the Brackish-Water-Adapted Cyanobacterium Nodularia spumigena CCY9414 Based on a Genome-Transcriptome Analysis

Peer reviewe

The Challenge of Regulation in a Minimal Photoautotroph: Non-Coding RNAs in Prochlorococcus

Prochlorococcus, an extremely small cyanobacterium that is very abundant in the world's oceans, has a very streamlined genome. On average, these cells have about 2,000 genes and very few regulatory proteins. The limited capability of regulation is thought to be a result of selection imposed by a relatively stable environment in combination with a very small genome. Furthermore, only ten non-coding RNAs (ncRNAs), which play crucial regulatory roles in all forms of life, have been described in Prochlorococcus. Most strains also lack the RNA chaperone Hfq, raising the question of how important this mode of regulation is for these cells. To explore this question, we examined the transcription of intergenic regions of Prochlorococcus MED4 cells subjected to a number of different stress conditions: changes in light qualities and quantities, phage infection, or phosphorus starvation. Analysis of Affymetrix microarray expression data from intergenic regions revealed 276 novel transcriptional units. Among these were 12 new ncRNAs, 24 antisense RNAs (asRNAs), as well as 113 short mRNAs. Two additional ncRNAs were identified by homology, and all 14 new ncRNAs were independently verified by Northern hybridization and 5′RACE. Unlike its reduced suite of regulatory proteins, the number of ncRNAs relative to genome size in Prochlorococcus is comparable to that found in other bacteria, suggesting that RNA regulators likely play a major role in regulation in this group. Moreover, the ncRNAs are concentrated in previously identified genomic islands, which carry genes of significance to the ecology of this organism, many of which are not of cyanobacterial origin. Expression profiles of some of these ncRNAs suggest involvement in light stress adaptation and/or the response to phage infection consistent with their location in the hypervariable genomic islands

The most common Chinese rhesus macaque MHC class I molecule shares peptide binding repertoire with the HLA-B7 supertype

Of the two rhesus macaque subspecies used for AIDS studies, the Simian immunodeficiency virus-infected Indian rhesus macaque (Macaca mulatta) is the most established model of HIV infection, providing both insight into pathogenesis and a system for testing novel vaccines. Despite the Chinese rhesus macaque potentially being a more relevant model for AIDS outcomes than the Indian rhesus macaque, the Chinese-origin rhesus macaques have not been well-characterized for their major histocompatibility complex (MHC) composition and function, reducing their greater utilization. In this study, we characterized a total of 50 unique Chinese rhesus macaques from several varying origins for their entire MHC class I allele composition and identified a total of 58 unique complete MHC class I sequences. Only nine of the sequences had been associated with Indian rhesus macaques, and 28/58 (48.3%) of the sequences identified were novel. From all MHC alleles detected, we prioritized Mamu-A1*02201 for functional characterization based on its higher frequency of expression. Upon the development of MHC/peptide binding assays and definition of its associated motif, we revealed that this allele shares peptide binding characteristics with the HLA-B7 supertype, the most frequent supertype in human populations. These studies provide the first functional characterization of an MHC class I molecule in the context of Chinese rhesus macaques and the first instance of HLA-B7 analogy for rhesus macaques

Functional analysis of frequently expressed Chinese rhesus macaque MHC class I molecules Mamu-A1*02601 and Mamu-B*08301 reveals HLA-A2 and HLA-A3 supertypic specificities

The Simian immunodeficiency virus (SIV)-infected Indian rhesus macaque (Macaca mulatta) is the most established model of HIV infection and AIDS-related research, despite the potential that macaques of Chinese origin is a more relevant model. Ongoing efforts to further characterize the Chinese rhesus macaques’ major histocompatibility complex (MHC) for composition and function should facilitate greater utilization of the species. Previous studies have demonstrated that Chinese-origin M. mulatta (Mamu) class I alleles are more polymorphic than their Indian counterparts, perhaps inferring a model more representative of human MHC, human leukocyte antigen (HLA). Furthermore, the Chinese rhesus macaque class I allele Mamu-A1*02201, the most frequent allele thus far identified, has recently been characterized and shown to be an HLA-B7 supertype analog, the most frequent supertype in human populations. In this study, we have characterized two additional alleles expressed with high frequency in Chinese rhesus macaques, Mamu-A1*02601 and Mamu-B*08301. Upon the development of MHC–peptide-binding assays and definition of their associated motifs, we reveal that these Mamu alleles share peptide-binding characteristics with the HLA-A2 and HLA-A3 supertypes, respectively, the next most frequent human supertypes after HLA-B7. These data suggest that Chinese rhesus macaques may indeed be a more representative model of HLA gene diversity and function as compared to the species of Indian origin and therefore a better model for investigating human immune responses

Transcript mapping based on dRNA-seq data

Background: RNA-seq and its variant differential RNA-seq (dRNA-seq) are today routine methods for transcriptome analysis in bacteria. While expression profiling and transcriptional start site prediction are standard tasks today, the problem of identifying transcriptional units in a genome-wide fashion is still not solved for prokaryotic systems. Results: We present RNASEG, an algorithm for the prediction of transcriptional units based on dRNA-seq data. A key feature of the algorithm is that, based on the data, it distinguishes between transcribed and un-transcribed genomic segments. Furthermore, the program provides many different predictions in a single run, which can be used to infer the significance of transcriptional units in a consensus procedure. We show the performance of our method based on a well-studied dRNA-seq data set for Helicobacter pylori. Conclusions: With our algorithm it is possible to identify operons and 5'- and 3'-UTRs in an automated fashion. This alleviates the need for labour intensive manual inspection and enables large-scale studies in the area of comparative transcriptomics